Urine Drug Screen False Positives

Urine drug screens aren't completely useless, but they have a number of limitations. Here is a table where I have compiled all of the false positive causing drugs I could find (pdf):

Update 4/22/2016:
Here are my sources:

I started with this paper which was I originally heard on EM Abstracts (Jan 2011):

Brahm NC, Yeager LL, Fox MD, Farmer KC, Palmer TA.
Commonly prescribed medications and potential false-positive urine drug screens.
Am J Health Syst Pharm. 2010 Aug 15;67(16):1344-50.

Special thanks to Jon Cole from Hennepin who made this fantastic video.

Other sources include:
UMHS Guidelines for Clinical Care May 2009

Standridge JB, Adams SM, Zotos AP.
Urine drug screening: a valuable office procedure.
Am Fam Physician. 2010 Mar 1;81(5):635-40.

Reisfield GM, Haddad J, Wilson GR, Johannsen LM, Voorhees KL, Chronister CW, Goldberger BA, Peele JD, Bertholf RL.
Failure of amoxicillin to produce false-positive urine screens for cocaine metabolite.
J Anal Toxicol. 2008 May;32(4):315-8.

Ly BT, Thornton SL, Buono C, Stone JA, Wu AH.
False-positive urine phencyclidine immunoassay screen result caused by interference by tramadol and its metabolites.
Ann Emerg Med. 2012 Jun;59(6):545-7.
doi: 10.1016/j.annemergmed.2011.08.013

Swift RM, Griffiths W, Cammera P.
False positive urine drug screens from quinine in tonic water.
Addict Behav. 1989;14(2):213-5.

Updates 5/1/2016
Reordered alphabetically
Added lamotragine -> PCP
Geraci MJ, Peele J, McCoy SL, Elias B. Phencyclidine false positive induced by lamotrigine (Lamictal®) on a rapid urine toxicology screen. Int J Emerg Med. 2010 Dec; 3(4): 327–331.

Added a few more -> PCP
Phencyclidine (PCP) Test Systems Executive Summary. Chemistry and Toxicology Devices. FDA
2013 Apr 25, Link.

Get What You Pay For & Pay for What You Get

This post is co-authored by Seth Trueger & Cedric Dark and also appears on Policy PrescriptionsSee also the related post on Narrow Networks (PolicyRx).

Andrew Sprung and I had a great conversation about Republican presidential candidate Donald Trump's claim that premiums are rising (see the Storify below). Our view: premiums are generally flat. There is a lot of variation around this, mostly geographic, and also largely based on whose premiums you're talking about. Comparing premiums from before Obamacare to today’s is like comparing 1995 and 2015 cell phone plans. [caption id="attachment_5826" align="alignleft" width="300"]Source: Lauren (Flickr/CC) Source: Lauren (Flickr/CC)[/caption] Yes, some people who were insured on the non-group market prior to the ACA saw their premiums go up significantly. But this is a meaningless critique. First, the fraction of people who had non-group plans prior to the ACA is (and still is) pretty small - about 5% in 2011 [source: KFF]. Second, remember that most people who have individual plans only have them for a fairly short period of time; most only enroll in a plan for 6-18 months, such as for a few months while searching for a job and until their next employer-sponsored plan kicks in (see this post for example). And while some were happy with their coverage, remember the two most important caveats to pre-ACA nongroup premiums:
  1. What did these plans cover?
  2. Who didn't these plans cover?
The first of these big problems: people who ostensibly had insurance would find that it didn't help them when they needed it, because they hit annual or lifetime benefits limits; certain medical problems or services weren't covered; or, the insurer cancelled their plan when they made a claim. Even in the best-case situation, remember how frustrating it is to deal with actually getting an insurance claim paid.
"If you think government healthcare is bad, wait until Comcast runs it." - Seth
Personal example #1: I (Seth) had cheap private insurance for a few years in med school after getting kicked off my parents plan well before age 26 (Thanks, Obama) and I paid $60+ a month for essentially useless coverage that didn't really cover anything. Fortunately, I never got sick and I only really needed my insurance to satisfy my school’s requirement (and, maybe, piece of mind. But not really). While we don't know how many people were "happy" with their pre-ACA plan, we can estimate. Per Andrew Sprung, about half of the 16% of people in the non-group market now have grandfathered plans... which is roughly 1/2 of 1/6 of 1/20 of the insurance market, so 1 in 240 insurance plans. The second of these major issues that arises when comparing premiums before and after the ACA: preexisting conditions. How many people were completely blocked from getting insurance because of a preexisting medical problem? And relatedly, how many people were either charged higher premiums because of a preexisting condition? Or, were only given a plan that didn’t cover anything remotely related to their preexisting condition? ("You can buy insurance from us but we won't cover surveillance or treatment for a relapse of your Hodgkin's Lymphoma.") Personal example #2: My (Seth’s) wife was previously charged more (plus had to do a ton of frustrating paperwork) for the preexisting condition of "having a pre-cancerous benign mole removed." Remember: private insurance companies aren’t incentivized to keep us healthy; they are incentivized to keep us healthy until we turn 65. While a small fraction of individuals now pay a little more for their premiums, their insurance actually now has to cover stuff; and, they aren't getting a discount by excluding all the people who have serious health problems (or benign moles). Given all these caveats, it's really remarkable that premiums are pretty much flat at all. Let’s consider one last thing. “Premium price" can mean a lot of things. Is it subsidized or unsubsidized? Subsidized premiums are most likely pretty flat, and are what individuals actually pay. Unsubsidized premiums have gone up, but not by as much as people like Trump claim. I'm the first to admit that probably the biggest question the ACA poses is: will premium subsidies simply cost too much? And so far, it doesn't seem like it.
We have a great review forthcoming from Laura Medford-Davis on this issue. Stay tuned! - Cedric
Premium subsidies are simply the price we pay for insuring millions and millions of Americans in a functioning market for non-group insurance. And let’s not forget the quasi-secret but much, much, larger subsidies we already provide to people insured through their employers. We shouldn’t decry subsidies for insurance bought on the market while spending hundreds of billions of dollars subsidizing employer-sponsored insurance.

EM Mindset: emDocs

from Rich Winters
Special thanks to Alex Koyfman for inviting me to write an EM Mindset essay, Alex and Manpreet Singh for editing & posting it, and Reuben Strayer for the referral.

The post:

Some early Twitter chatter:

Streetlights & Counting Clicks

Someone recently sent me this 2014 Time Magazine article on metrics for web readership by Tony Haile, the CEO of Chartbeat, which does web metrics.

My first impression: this article seemed oddly familiar and I realized I read a similar article about Chartbeat by Farzad Manjoo in 2013 (with some of the exact same/similar graphs; note that this is not so much of a critique as just amusing to me):

Different articles, same graph. Bonus: see what's on Seth's bookmark bar

Technically different but essentially the same graphs. 

Go read either or both of these articles and come back here for my thoughts.

My key impressions:

-Of course neither clicks nor social media shares are a completely accurate proxy for what we really care about: engaged readers who understand, learn, and remember the content of an article

-but clicks and social media shares are (most likely) useful proxies.

Ultimately this is my more optimistic view of the "streetlight effect" -- sometimes it makes sense to look for your keys in the the light, where it's easy. See also: fruit, low-hanging.


Newspaper circulation: of course 1.4 million NY Times readers are not fully apprised of every topic discussed in each daily paper.

Symplur impressions: #ACEP14 had 33 million impressions; this does not mean that, on average, each emergency physician learned 1,000 things via Twitter during ACEP.

My take is that in all of these cases, of course there are limitations but these numbers are a "ceiling" -- an upper limit of theoretical impact, and they are still somewhat useful to compare numbers (e.g. one outlet's performance across time, or multiple outlets' performance against each other).

The rub is how accurate the surrogate marker is as a proxy. Compare impact factor, where it's probably useless to compare a clinical EM journal against an academic mathematics journal, where citations accrue at different rates and may signify more or less (for more on limitations of journal impact factor, see our piece on Altmetric).

Complete speculation: I suspect that clicks are a useful measure for Annals of EM, particularly as we have what seem to be fairly high visit durations (nearly 3 minutes) and 2.6 pageviews per visit (if I'm reading the data I have correctly).

I have not analyzed this formally in any way, but casually following Annals' top Altmetric score articles seems to give a handful of popular topics, in no particular order:

1) airway (always a popular topic, particularly on social media)

2) social media (tons of self promotion and mutual congratulations, as well as legitimate interest in social media)

3) public health (e.g. ACA, injury and violence, even Ebola)

I suspect the social-media-share-to-actual-reading ratio rises going down this list, particularly as there are a lot of overlapping online communities and general public interest in public health topics.

One last point about the Time article:

2/3 of reading is below the fold, which makes sense: the overwhelming majority of clicks result in 15 seconds or less of reading, but the small fraction who read below the fold spend much, much more time, just as half of Medicare spending is on 5% of beneficiaries.